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Author's Personal Copy Author's personal copy J Insect Conserv 3OI 10.1007/s10841-014-9649-1 ORIGINALPAPER A spider diversity model for the Caucasus Ecoregion Giorgi Chaladze • Stefan Otto • Sebastian Tramp Received: 27 June 2013 / Accepted: 16 June 2014 � Springer International Publishing Switzerland 2014 Abstract Precise information on spatial patterns !( spe- invertebrate taxa in the Caucasus Ecoregion is needed to cies richnes$ and endemic species distribution is import nt improve conservation efforts in this biodiversity hotspot. for effective species conservation. In the Caucasus Ecore- gion such information is virtually non-existent for inver- Keywords Arane e� Biodiversity� Climatic variable$� tebrate taxa. /sing occurrence data from large database Spatial patterns� Altitudinal gradient� Caucasus &e calculated species distribution )ode"$ &ith the GARP Ecoregion� G"!# " hotspots algorithm for 471 spider species to visualize the diversity distribution !( spider species in this region. Overal" species diversity & $ highest in mountain forest$ !( the North Introduction Caucasus, east-central Georgia, the southern slopes !( the eastern Great Caucasus and south-east Azerbaijan. A In order to halt ongoing #iodiversity "!$$0 conservation regression tree analysis Chi squared automatic interaction efforts are often focussed using cross-country conservati!n detector method revealed the mean temperature !( the plans and biodiver$ity ction plan$0 &hich are based on driest quarter and precipitation parameters to be the ) in existing threats to #iodiversity in the region and precise environmental factor$ shaping these patterns. 3iversity !( information on the distribution !( species (Ceball!$ and endemic species & $ correlated &ith overa"" species Brown 1995: Garcı< 2006: Newbold et "+ 2009: Arponen diversity but hotspots !( endemic species (10? percent !( 20125+ 3ue to lack !( research on arthropod taxa, con- "" species) exists in high-mountain areas, suggesting post* servation plans do not n!rmally include arthropod species glacia" speciation events in the high mountains $ the ) in to an extent reflecting their outstanding contribution to the sources !( high endemi$) in Caucasus. Further informa- overall species diversity+ ?his in turn leads to conservati!n tion on the spatial distribution !( species diversity !( efforts, &hich d! not effective"- cover areas important (!r arthropod diversity 4@erna<ndez-Manrique et "+ 20125 and therefore proba#"- result in dramatic ""- increased diversity "!$$ &ithin this taxon, and hence !verall species & G+ Chaladze 4 5 diversity. In order to actually halt current diversity "!$$0 it Institute !( Ecology0 Ilia State /niversity, 3/5 ,%!"!= $%vili Ave., 0162 ?bilisi, Georgia is therefore necessar- to stud- patterns !( rthropod e-mail: [email protected] diversity more intensivel- and use the obtained insights in updated conservation plans and biodiversity action plans S. Otto (Card!$! et "+ 2008: 3iniz-Fi"%! et "+ 2010: Beck et "+ 3epartment !( Animal Ecology and ?ropica" Biology, /niversity FuGrzburg, GutsMuthsstr. 42, 04177 Leipzig, 2012: @erna<ndez-Manrique et "+ 20125+ Germany Because !( it$ importance $ one !( the &!rldwide 7iodi* versit- @!tspot$ 4Ayers et "+ 2000: Cier et "+ 2005: 6!$ter- S. ?ramp ?ur"ey and G!=%el $hivili 2009: D 'ani$%vili and A ""on 3epartment !( ,!)puter Science, Business Information Systems, /niversity Leipzig, Augustusplatz 10, Dimmer P614, 200950 nu)ber !( conservation and action plan$ % ve been 04109 Leipzig, Germany pu#"i$%ed &ithin the , uc $us Ecoregion 4%ence(!rt% termed 123 Author's personal copy J Insect Conserv CE5 4AEPNR 2005: Fi""ia)$ et "+ 2006: MEPNR 20115+ taxon. @!&ever, recent study modeled the distribution !( 3espite high tota" nu)#er$ !( specie$ and high rate$ !( ant species richnes$ in Georgia 4,haladze 201250 facilitat- endemi$) )!ng rthropods (Aliyev et "+ 2009: C " $%ian ing new hypotheses on the location !( arthropod diversity 2009: C!nstantinov et "+ 2009: D ' ni$%vi"i and A ""on hotspots in this country. Next to intensified field &ork, it is 200950 including spider$ 4Hsnel et "+ 200850 kn!&ledge #out important that more studies retrieve the richnes$ !( existing spatia" patterns !( rthropod species diver$it- in the ,E is occurrence data nd provide distribution map$ !( the virtua""- nonexistent. In order to give the arthropods their diversity !( additional arthropod ta. + /sing such maps !( deserved &eight (!r conservation ef(!rt$ in thi$ region0 it i$ different arthropod species to create spatia" representations important t! cl!$e thi$ dat gap #- #!th intensified researc% $ !( the overa"" arthropod diversity should yield the infor- &e"" $ #- ) king t%e existing data avai" #"e in free"- mation needed to give the highly diverse arthropods their acce$$i#"e data# se$+ A$ Ott! and ?ramp 420125 $%!&ed (!r deserved status in future conservation plans for the CE+ spider$ in the CE0 reviewing the existing literature (!r given In the present paper &e aim to contribute to this goal #- ta.!n and compiling these occurrence data int! data# se can providing spatial )ode"$ !( overall and endemic spider dr )atic ""- increase the nu)#er !( kn!&n occurrence$ and species diversity # sed on SDA$+ Fe think that spiders are update the specie$ list$ (!r the relevant countries in thi$ region good mode" taxon (or this study because region " and 4Aik% i"!v 2002: A rusi= et "+ 2006: H$ne" et "+ 20085+ continental spider diversity patterns can be explained to A " rge amount !( !ccurrence data !( sufficient 2uality large extent #- environmental factor$ (Jime<nez-Jalverde is often insufficient on its !&n to derive the information and L!#! 2007: Finch et "+ 2008: Jime<nez-Valverde et "+ needed for effective species conservation. In order to 2010: Carvalho et "+ 201250 common"- included in SDA identify hotspots !( rthropod diversity0 endemic species !r approaches, e.g. climatic and topographic factor$+ @ere &e threatened specie$0 the occurrence data must be transl ted aim to answer the (!""!&ing questions: into spatia" mode"$ !( distribution for every species0 (1) Fhat is the predicted spatial pattern !( spider species resulting in map$ highlighting areas !( high arthropod richnes$ in the CEL diversity. Macroecologica" methods like specie$ distribu- (2) Fhere are predicted %!tspots !( spider diversit- tion modeling (SDM) can bridge this gap between existing located in the CEL occurrence data nd the fin " distribution ) ps (Arau<1! and (3) Fhere are predicted %!tspots !( endemic spider Peterson 20125+ In S3A0 species !ccurrence dat can be diversity located in the CEL correlated &ith #iotic 4$cenopoetic), #iotic and )ovement (4) Fhere are regions predicted to $%!& extraordinarily factor$ (biogeogr phic and migratory) in the region !( high proportions !( endemic spider species in the interest0 in order calculate spatial )ode" !( the area !( CE? distribution &ith suitable conditions for this species (Syp- 495 Fhat are the underlying factor$ shaping these hard and Franklin 2009: Graham et "+ 2010: Sobero<n 2010: patterns? Dimmermann et "+ 2010: Jasconcelos et "+ 20125+ Recent algorithm$ and statistical methods have helped t! develop spatial )!de"$ describing biodiversity including those developed for the prediction !( species distributions aterials and methods (Stockwell and Peters 1999: Soberon and Peterson 2005: Fitzpatrick et "+ 2007: Ortega-Huerta nd Peterson 2008: Study area de Souz MunK!' et "+ 20115+ In order to identify the spatia" pattern !( species richnes$0 distribution )!de"$ for single ?he study area include$ the politica" territories !( Georgia, species are developed and then stacked (Garcı< 2006: Armenia, Azerbaijan $ &ell $ the countries !( the North New#!"d et "+ 2009: ,% " dze 20125+ An alternative Caucasus and the rayon$ Crasnodar and Stavropol in method is recording species richnes$ t individual localities Southern Russia 46ig. 15+ ?%e CE is situated on the and modeling richness patterns directly. Newbold et "+ boundar- !( temperate and moist-temperate climate belts. 420095 compared the tw! approache$ &hile modeling the 3ue to the dominance !( it$ mountainous regions, the cli- butter>- and ) )) " fauna !( Egypt. ?hey $%!&ed that matic conditions in the CE are very diverse, ranging from using the former approach (summing individual )ode"$5 &arm nd moist regions &ith precipitation !( more than produce$ more accurate output. Summing individual 2,000 )) per year near the Black Se Coast to semi-arid models is good approach only &hen the available dis- regions in Azerbaijan, receiving only 250 )) annual tribution data re $ufficient to create individual specie$ precipitation (see det ils in Filliams et "+ 420065+ distribution models+ ?ogether &ith this orographic and climatic comple.ity Species distribution modeling % $ rarely been applied in the CE is ric% in landscape type$ !( number !( terrestrial the CE to visualize the spatial distribution !( an arthropod ecosystems: mountain forests, freshwater and marine 123 Author's personal copy J Insect Conserv !ig. # Study are + Spots indicate unique localities &ith !ccurrence data ecosystems, dry )!untain shrublands, steppes, semidesert$0 precipitation seas!nality, (16) precipitation !( wettest &etlands and %igh-mountains, &hich contribute to the quarter0 (17) precipitation !( driest quarter0 (18) precipit * outstanding biodiversity !( the CE (Myers et "+ 2000: tion !( warmest quarter0 and (19) precipitation !( coldest Fillia)$ et "+ 2006: Foster-Turley and G!=%elashivili quarter+ 2009: Dazanishvili and Mallon 20095+ Range mode"$ &ere developed
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